Teaching Resources

Cognitive Science

Minds & Machines

This honours elective (PSYC4103) provides a gentle introduction to computational modelling of human cognition. It is structured around a series of case studies covering, inductive reasoning, concept learning, decision making and language acquisition. As such, discussions focus on whether - and how - the comparison between human and the machine learning tells us something useful about the mind.

R for Psychological Science

Research methods in psychology have traditionally focused on study design and statistical analysis. The R statistical programming language is well-suited to these problems, but it's also very handy for solving many other problems facing behavioural scientists. This resource provides an introduction to R programming, with applications in psychological science. (Linked with the PSYC3361 internship program)

Perception & Cognition

This lecture series is part of PSYC2071, and provides an introduction to cognitive psychology. The lecture materials present a brief history to the field, and then discuss key ideas in human attention, categorisation and reasoning. The content varies a little from year to year, but the slides below are representative:

Learning Statistics with R

From 2011 to 2015 I used to teach introductory statistics, using the R statistical computing language, and wrote my own lecture notes, pitched at undergraduate psychology students. The notes became quite extensive, and are now effectively a book.

Computational Cognitive Science

From 2010 to 2014 we (Amy and Dani) used to run an introduction to computational cognitive science for undergraduate computer science students. The class hasn't been run in a few years, but we've archived most of the content.